> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/elevenlabs/elevenlabs-python/llms.txt
> Use this file to discover all available pages before exploring further.

# Models

> Available text-to-speech models and their capabilities

ElevenLabs offers multiple state-of-the-art TTS models, each optimized for different use cases, languages, and performance requirements.

## Listing Available Models

Retrieve all available models for your account:

```python theme={null}
from elevenlabs.client import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY"
)

models = client.models.list()

for model in models:
    print(f"Model: {model.model_id}")
    print(f"Name: {model.name}")
    print(f"Languages: {len(model.languages)} supported")
    print(f"Can do TTS: {model.can_do_text_to_speech}")
    print("---")
```

## Main Models Overview

ElevenLabs provides four main TTS models, each with unique characteristics:

<CardGroup cols={2}>
  <Card title="Eleven v3" icon="star">
    **Model ID:** `eleven_v3`

    Dramatic delivery and performances with support for 70+ languages and natural multi-speaker dialogue.
  </Card>

  <Card title="Eleven Multilingual v2" icon="globe">
    **Model ID:** `eleven_multilingual_v2`

    Excels in stability, language diversity, and accent accuracy across 29 languages. Recommended for most use cases.
  </Card>

  <Card title="Eleven Flash v2.5" icon="bolt">
    **Model ID:** `eleven_flash_v2_5`

    Ultra-low latency with support for 32 languages. Faster model at 50% lower price per character.
  </Card>

  <Card title="Eleven Turbo v2.5" icon="gauge-high">
    **Model ID:** `eleven_turbo_v2_5`

    Good balance of quality and latency, ideal for developer use cases where speed is crucial. Supports 32 languages.
  </Card>
</CardGroup>

## Eleven v3

The latest generation model with dramatic performances and extensive language support.

```python theme={null}
audio = client.text_to_speech.convert(
    text="Experience the most dramatic and lifelike performances.",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_v3",
    output_format="mp3_44100_128"
)
```

### Key Features

<AccordionGroup>
  <Accordion title="Dramatic Delivery">
    Eleven v3 excels at emotional expression and dramatic performances, making it ideal for:

    * Audiobook narration
    * Character voices
    * Storytelling
    * Expressive dialogue
  </Accordion>

  <Accordion title="70+ Languages">
    The most multilingual model with support for over 70 languages, providing global reach for your applications.
  </Accordion>

  <Accordion title="Multi-Speaker Support">
    Natural multi-speaker dialogue capabilities for:

    * Conversational AI
    * Podcast generation
    * Interview simulations
    * Interactive narratives
  </Accordion>
</AccordionGroup>

<Warning>
  Eleven v3 may have higher latency compared to Flash or Turbo models. Not recommended for real-time streaming applications where low latency is critical.
</Warning>

## Eleven Multilingual v2

The recommended model for most production use cases, balancing quality, stability, and language support.

```python theme={null}
audio = client.text_to_speech.convert(
    text="The first move is what sets everything in motion.",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_multilingual_v2",
    output_format="mp3_44100_128"
)
```

### Key Features

* **Stability:** Consistent voice quality across generations
* **Accuracy:** Excellent accent and pronunciation accuracy
* **29 Languages:** Broad language support for global applications
* **Reliability:** Proven performance in production environments

### Use Cases

<CardGroup cols={2}>
  <Card title="Content Creation">
    * Video voiceovers
    * E-learning modules
    * Marketing materials
    * Product demos
  </Card>

  <Card title="Applications">
    * Mobile apps
    * Web applications
    * IVR systems
    * Accessibility tools
  </Card>
</CardGroup>

## Eleven Flash v2.5

Ultra-low latency model optimized for speed and cost efficiency.

```python theme={null}
audio = client.text_to_speech.convert(
    text="Fast generation with minimal latency.",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_flash_v2_5",
    output_format="mp3_22050_32"  # Lower format for even faster streaming
)
```

### Key Features

* **Ultra-Low Latency:** Fastest generation times
* **Cost Effective:** 50% lower price per character
* **32 Languages:** Broad language support
* **Optimized for Streaming:** Ideal for real-time applications

### Best For

<Steps>
  <Step title="Real-Time Streaming">
    Low-latency audio streaming for conversational AI and live applications
  </Step>

  <Step title="High-Volume Processing">
    Batch processing large amounts of text with cost constraints
  </Step>

  <Step title="Prototyping">
    Rapid development and testing with quick iteration cycles
  </Step>
</Steps>

```python theme={null}
# Optimized for streaming
audio_stream = client.text_to_speech.stream(
    text="Real-time streaming with Flash v2.5",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_flash_v2_5",
    optimize_streaming_latency=4
)
```

## Eleven Turbo v2.5

Balanced model providing excellent quality-to-speed ratio for developer applications.

```python theme={null}
audio = client.text_to_speech.convert(
    text="Great balance of quality and latency.",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_turbo_v2_5",
    output_format="mp3_44100_128"
)
```

### Key Features

* **Balanced Performance:** Good quality with reduced latency
* **Developer-Focused:** Optimized for common development scenarios
* **32 Languages:** Wide language coverage
* **Versatile:** Suitable for most application types

### Ideal Use Cases

* **Conversational AI:** Chatbots and virtual assistants
* **Gaming:** Character dialogue and narration
* **Notifications:** Audio alerts and announcements
* **Interactive Systems:** IVR and phone systems

## Model Comparison

<ResponseField name="Model Characteristics" type="comparison">
  | Feature           | v3               | Multilingual v2 | Flash v2.5     | Turbo v2.5     |
  | ----------------- | ---------------- | --------------- | -------------- | -------------- |
  | **Quality**       | Highest          | High            | Good           | High           |
  | **Latency**       | Higher           | Medium          | Lowest         | Low            |
  | **Languages**     | 70+              | 29              | 32             | 32             |
  | **Price**         | Standard         | Standard        | 50% lower      | Standard       |
  | **Best For**      | Dramatic content | Production      | Real-time/Cost | Developer apps |
  | **Multi-speaker** | Yes              | Limited         | No             | Limited        |
</ResponseField>

## Choosing the Right Model

<Steps>
  <Step title="Assess Your Requirements">
    Determine your priorities: quality, latency, cost, or language support
  </Step>

  <Step title="Consider Your Use Case">
    * **Content creation** → Multilingual v2 or v3
    * **Real-time streaming** → Flash v2.5 or Turbo v2.5
    * **High-volume processing** → Flash v2.5
    * **Dramatic narration** → v3
  </Step>

  <Step title="Test and Compare">
    ```python theme={null}
    models_to_test = [
        "eleven_v3",
        "eleven_multilingual_v2",
        "eleven_flash_v2_5",
        "eleven_turbo_v2_5"
    ]

    for model_id in models_to_test:
        audio = client.text_to_speech.convert(
            text="Compare model outputs.",
            voice_id="JBFqnCBsd6RMkjVDRZzb",
            model_id=model_id
        )
        # Save and compare
        save(audio, f"output_{model_id}.mp3")
    ```
  </Step>
</Steps>

## Language Support

Check which languages a model supports:

```python theme={null}
models = client.models.list()

for model in models:
    if model.model_id == "eleven_v3":
        print(f"Languages supported by {model.name}:")
        for lang in model.languages:
            print(f"  - {lang.name} ({lang.language_id})")
```

## Model-Specific Settings

Some models support additional parameters:

```python theme={null}
# Using language code enforcement
audio = client.text_to_speech.convert(
    text="Bonjour le monde",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_multilingual_v2",
    language_code="fr"  # Enforce French
)

# Optimizing for streaming with Turbo
audio_stream = client.text_to_speech.stream(
    text="Optimized streaming.",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_turbo_v2_5",
    optimize_streaming_latency=3
)
```

## Async Model Operations

List models asynchronously:

```python theme={null}
import asyncio
from elevenlabs.client import AsyncElevenLabs

client = AsyncElevenLabs(
    api_key="YOUR_API_KEY"
)

async def print_models():
    models = await client.models.list()
    for model in models:
        print(f"{model.name}: {model.model_id}")

asyncio.run(print_models())
```

## Best Practices

<AccordionGroup>
  <Accordion title="Production Deployments">
    * Use **Multilingual v2** for stable, production-ready applications
    * Test with your actual content before committing to a model
    * Monitor usage and costs across different models
    * Consider fallback strategies if a model is unavailable
  </Accordion>

  <Accordion title="Real-Time Applications">
    * Choose **Flash v2.5** or **Turbo v2.5** for low-latency requirements
    * Combine with `optimize_streaming_latency` parameter
    * Use lower output formats (22050Hz, 32kbps) to reduce bandwidth
    * Implement proper error handling and retry logic
  </Accordion>

  <Accordion title="Cost Optimization">
    * Use **Flash v2.5** for high-volume processing (50% cost savings)
    * Cache generated audio when possible
    * Monitor character usage across models
    * Batch requests when real-time isn't required
  </Accordion>

  <Accordion title="Quality Maximization">
    * Use **v3** for the highest quality and dramatic expression
    * Use higher output formats (44100Hz, 128kbps+)
    * Fine-tune voice settings for each model
    * Test different models with your specific content
  </Accordion>
</AccordionGroup>

## Additional Resources

<CardGroup cols={2}>
  <Card title="Models Documentation" icon="book" href="https://elevenlabs.io/docs/models">
    Detailed information about all models and languages
  </Card>

  <Card title="Voice Lab" icon="flask" href="https://elevenlabs.io/voice-lab">
    Try different models with various voices
  </Card>
</CardGroup>

<Note>
  For the most up-to-date information about model capabilities, pricing, and language support, visit the [ElevenLabs Models documentation](https://elevenlabs.io/docs/models).
</Note>